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🧵Our unique full-stack approach to AI lets us deliver powerful, cost-efficient products to developers and everyday users. But what exactly does it mean when a technology system is "full-stack,” and why is it so important to our approach? We talked to @rseroter, senior director and chief evangelist at @googlecloud, to break it all down 👇 Where does the phrase “full-stack” come from, and what does it mean when we’re talking about tech? @rseroter: The term "full-stack" originally came out in software development a decade or so ago — usually in regard to applications. Historically, building an app required multiple specialized teams: a front-end developer to build beautiful user interfaces, a back-end developer to handle server-side logic and a dedicated database team. The concept of a "full-stack engineer" emerged to describe a developer who could work across all of these functions independently. Instead of constantly handing off components from one person to another, a full-stack engineer could take an idea from a rough concept all the way to a fully running piece of software.

every App Store rejection costs you 2-5 days. so we built a cli that scans your iOS app against apple's guidelines before you submit. > payment & IAP compliance > privacy manifests & data declarations > required sign-in & account deletion flows > metadata & completeness checks > binary validation now with a added cloud device feature, so it validates full user flows, not just the binary. made it a claude code and codex skill. it fixes every issue it finds. scan, fix, repeat until it passes.

Data centers are being blamed for rising US power bills, but outdated policy may be the real culprit. Doug Arent of the Center on Global Energy Policy explains how poor incentives are shaping electricity costs

USAID: The data show that dismantling USAID did not result in ANY increase in African mortality much less the four million Democrats claim Elon Musk is responsible for killing. It was all a lie. In fact, the UNAIDS/SAMRC data show that mortality declined after. h/t @arctotherium42

All Paid Courses (Free for First 4500 People). 𝗣𝗮𝗶𝗱 𝗖𝗼𝘂𝗿𝘀𝗲 𝗙𝗥𝗘𝗘 (PART - 1) 1. Artificial Intelligence 2. Machine Learning 3. Prompt Engineering 4. Claude,Chatgpt,Grok 5. Data Analytics 6. AWS Certified 7. Data Science 8. BIG DATA 9. Python 10. Ethical Hacking (72 Hours only ) Like + RT + comment ' Drive ' Must Follow me so I can DM you.

QVAC SDK 0.14.0 is live. This release makes the on-device stack faster on mobile, ships the developer-agent path, and takes local text-to-speech to 31 languages. Main highlights: - OpenCode and OpenClaw. The first official OpenCode plugin, plus a maintained OpenClaw compatibility path, both built on managed mode and qvac serve. Point a coding agent at a local model with far less setup and far fewer surprises. - Brain-computer interface transcription, on the SDK. Take recorded neural signal data and decode it into text, fully on-device, no cloud. Stream it in chunks through a simple API. In 0.14 it runs GPU-accelerated on iOS. - Text to Speech in 31 languages with our Supertonic3 upgrade. VOICE AND SPEECH - Supertonic3 multilingual TTS, 5 languages to 31. - Chatterbox and Supertonic now run on the Android GPU, with lower memory use (especially on iOS), quantized s3gen Chatterbox support, and a fix for Chatterbox occasionally emitting random speech. - Whisper transcription now runs on the iOS GPU. Parakeet runs on the Android GPU, with steadier real-time streaming. VISION AND OCR - VLM multi-tile batching: high-resolution Pan and Scan images are encoded in one pass instead of tile by tile, for faster vision throughput. - OCR on ggml (EasyOCR and DocTR) reaches full speed parity with the onnx path, across Metal, OpenCL, and Vulkan. PLATFORM AND RELIABILITY - Dynamic compute backends on Linux: one build picks the right backend at runtime, and opens the door to ROCm and CUDA support without per-backend builds. - Thinking tokens are kept out of the model context, so reasoning no longer fills the KV cache. SDK 0.14.0 is now leaner and faster to start. Let’s build.

📊 Investors brace for key US data in a shortened week. What could payrolls and inflation signals mean for markets? Tune in to the Reuters Morning Bid podcast

My entire AI stack is now Chinese 🇨🇳 87% cheaper. same revenue swaps by task: 1. reasoning / backend brain Opus 4.8 → Kimi K2.7 benchmark gap: ~8% · price: ~11x cheaper 2. code generation GPT-5.5 → Qwen 3.7 Max benchmark gap: ~18% · price: ~7x cheaper 3. agent loops + tool calling Sonnet 4.7 → GLM 5.2 benchmark gap: ~3% · price: ~5x cheaper on input 4. cheap volume / bulk processing GPT-5.5 mini → MiMo V2.5 benchmark gap: ~6% · price: ~12x cheaper 5. image generation GPT-Image-2 → Wan 2.5 benchmark gap: ~5% · price: ~8x cheaper 6. video generation Sora 2 → Kling 3.0 benchmark gap: roughly equal · price: ~6x cheaper [ result after 30 days: ] operating costs dropped 87%, output quality dropped 4% on average, revenue unchanged the most important that these models will be not banned in a month and i can run them locally nobody will steal my data and i can learn them as i need full article drops tomorrow with: > exact routing logic per task type > the 2 cases where I still pay for American > the migration playbook anyone can copy in a weekend VERY IMPORTANT to get migrated now, while it's not too late